Data Scientist

Job description Who we are About the role: Samsara Technologies India Private Limited is seeking a Data Scientist to advance our data-driven efforts in sales, marketing, and customer success. As part of the Data Science and AI team in Revenue Operations, this role focuses on designing and delivering predictive models, refining AI-based scripts to validate, augment, and test the accuracy of business critical data, and establishing the quality measurement, lineage, and input pipelines of that data. You ll collaborate closely with stakeholders in BizTech, Marketing, Sales, and Operations to unlock insights, automate processes, and enhance the operational efficiency of the sales organization. This hybrid position requires 3 days per week in our Bangalore office and 2 days working remotely. This position requires working hours in IST. Relocation assistance will not be provided for this role. You should apply if: You want to impact the industries that run our world: Your efforts will result in real-world impact helping to keep the lights on, get food into grocery stores, and most importantly, ensure workers return home safely. You have an innate curiosity about how businesses work: One day you ll meet with someone in waste management and the next you may be learning about the inner workings of a food distribution center. Our top sales team members seek to learn the ins and outs of the businesses they support in order to make a larger impact. You build genuine relationships with your customers: The industries we serve have relied on pen-and-paper solutions for years and haven t been met with the type of technology we offer. Our customers value earned trust and human relationships built over time. You want to be with the best: Samsara s high-performance culture means you ll be surrounded by the best and challenged to go farther than you have before. You are a team player: At Samsara, sales is a team sport. We help each other out by sharing best practices and focusing on winning as a team. In this role, you will: Estimate revenue opportunity models and conduct impact analysis as part of the annual strategic planning cycle to guide GTM and investment decisions. Leverage LLMs and other AI tools to systematically validate account-level data, enabling dynamic quality measurement scores and continuous trust in business-critical data. Generate predictive models and triangulate from multiple inputs CRMs, web data, third-party signals to drive data accuracy and establish reliable sources of truth. Establish scalable data pipelines from internal systems to generate and sustain baseline data programs supporting cross-functional initiatives. Contribute to the development of predictive analytics tools , such as sales performance dashboards, pipeline forecasting models, and KPI frameworks, to enhance operational efficiency. Collaborate cross-functionally with Sales, Marketing Ops, BizTech, and Enablement teams to automate insights, enrich GTM execution, and accelerate business outcomes. Champion, role model, and embed Samsara s cultural principles Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team as we scale globally and across new offices. Minimum requirements for the role: Bachelor s or Master s degree in Computer Science, Data Science, Statistics, or a related field. 6+ years of experience in data science, AI engineering, or advanced analytics roles. Proficiency in Python, SQL, and tools such as Tableau for building analytics and dashboards. Experience developing and deploying ML models to support sales/revenue strategies. Hands-on experience with CRMs and sales/marketing data pipelines. Exposure to LLM-based tools and GenAI for data enrichment or automation tasks. Strong analytical, communication, and project management skills. An ideal candidate also has: Familiarity with MLOps tools (Docker, Kubernetes), model versioning, and deployment workflows. Experience with AI observability, monitoring, and guardrail implementation for responsible AI. Exposure to ETL/data engineering processes